Darknetpy is a simple binding for darknet's yolo (v4) detector.
Install it from pypi
curl https://sh.rustup.rs -sSf | sh
rustup default nightly
pip install darknetpy
Install a pre-built binary
pip install https://github.com/danielgatis/darknetpy/raw/master/dist/darknetpy-4.2-cp37-cp37m-linux_x86_64.whl
GPU=1 pip install darknetpy
to build with CUDA to accelerate by using GPU (CUDA should be in /use/local/cuda).
CUDNN=1 pip install darknetpy
to build with cuDNN to accelerate training by using GPU (cuDNN should be in /usr/local/cudnn).
OPENCV=1 pip install darknetpy
to build with OpenCV.
OPENMP=1 pip install darknetpy
to build with OpenMP support to accelerate Yolo by using multi-core CPU.
In example.py:
from darknetpy.detector import Detector detector = Detector('<absolute-path-to>/darknet/cfg/coco.data', '<absolute-path-to>/darknet/cfg/yolo.cfg', '<absolute-path-to>/darknet/yolo.weights') results = detector.detect('<absolute-path-to>/darknet/data/dog.jpg') print(results)
Runing:
python example.py
Result:
[{'right': 194, 'bottom': 353, 'top': 264, 'class': 'dog', 'prob': 0.8198755383491516, 'left': 71}]
On the project root directory
docker run --rm -v `pwd`:/io quay.io/pypa/manylinux2010_x86_64 /io/build-wheels.sh
Liked some of my work? Buy me a coffee (or more likely a beer)